Object detection, instance segmentation, keypoints, classification
When comparing CVAT to VGG Image Annotator (VIA), both tools support core annotation tasks such as bounding boxes, polygons, and classification. But they differ significantly in scale, usability, and workflow capabilities. CVAT, created by Intel, is a more advanced, web-based tool designed for team collaboration and high-volume labeling, with features like keyframe interpolation for video, keyboard shortcuts, and role-based access control. VIA, developed by Oxford’s Visual Geometry Group, is a lightweight, in-browser tool best suited for quick, single-user annotation projects. It requires no installation and works offline, but lacks features like team management, analytics, or model integration.
Here are the key differences:
VIA is ideal for quick, one-off projects or educational use where simplicity is key. CVAT is better suited for structured, collaborative workflows involving large datasets or video. Both tools can be extended with comprehensive computer vision platforms such as Roboflow to unlock model training, augmentation, and deployment capabilities.
